This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Background

Recent data support the beneficial role of gesturing during mental practice. The present
study examined whether coupling motor imagery (MI) with some movement sequences (dynamic
imagery condition) impacted motor performance to a greater extent than performing
MI while remaining motionless.

Methods

A group of active high jumpers imagined their jump both with and without associated
arm movement. Three outcome variables were measured: the number of successful attempts,
the temporal congruence between MI and actual jump performance, and the technical
quality of the jump.

Results

Data revealed that dynamic imagery enhanced both MI quality and temporal congruence
between MI and motor performance, and further improved the technical efficacy of the
jump. Athletes also reported more vivid representation while coupling MI with actual
movement.

Conclusions

These data support the hypothesis that performing dynamic imagery might contribute
to enhance MI quality and efficacy, and sketch potentially fruitful new directions
for MI practice.

Keywords:

Background

Motor imagery (MI) is one of the remarkable capacities of the mind enabling everyone
to mentally simulate an action without engaging in actual physical execution [1]. MI and physical practice share similar neural substrate, albeit corresponding neural
networks are not totally overlapping [2-5], hence supporting the principle of functional equivalence [6]. Based on this concept, the efficacy of an imagery intervention is thought to depend
on this abstract idea of neural similarity between MI and motor performance. From
a practical viewpoint, previous experimental research provided evidence that MI contributes
to improve performance in athletes and to promote recovery from injury (for reviews,
[7-12]). Interestingly, unless MI is congruent with physical practice, it will not be as
effective in achieving its desired effects. For example, it is now well-known that
physical experience is important before engaging in MI. At a neural level, it may
probably contribute to a greater overlap between MI and motor performance. So far,
several MI models have been designed to provide a detailed description of the key-components
of the MI content to ascertain its efficacy, and contribute to develop more effective
imagery interventions (e.g., the PETTLEP model [6] and the MIIMS model [9]).

Among others, motor execution issues during MI should be close to those related to
actual execution, that is, the spatial and temporal characteristics should be preserved
during MI [13]. For instance, preserving the temporal accuracy during mental rehearsal is required
to avoid harmful alterations of the actual movement timing. Indeed, imagining a motor
sequence either at a slower or faster pace might affect the corresponding actual movement
speed [14-16]. Conversely, MI speed is not a crucial factor when integrating in imagery sequences
with a motivational outcome, and some athletes occasionally reported using voluntarily
slow, real-time and fast MI to achieve different outcomes [17]. Likewise, athletes frequently imagine their pending motor performance while adopting
the same position as that required by its physical execution, which is believed to
facilitate the MI process [18,19]. The environment or context in which MI is performed is also likely to facilitate
the mental operations required to form accurate and vivid mental images [20,21].

With reference to the definition we gave in the above paragraphs, the participants
are usually requested to perform MI in the absence of movement during mental rehearsal
sequences [22]. A large amount of imagery interventions therefore decoupled MI from the action,
and experimental designs even checked with electromyography that participants did
not contract any muscles during MI. A subliminal muscle activity has been, however,
frequently recorded during MI, which suggests that the motor command is probably not
fully inhibited. Guillot et al. [23] and Lebon et al. [24] reported that the subliminal muscle responses during MI of concentric, isometric
and eccentric contractions typically mirrored the configuration of the muscle activity
recorded during actual practice. This issue contributes to support that mental representation
is very close to actual practice, and that moving while imagining a given action might
be possible. Moreover, the recent “motor cognition” theory considers MI as being placed
along a continuum where intentional movement is on one side and representation at
the opposite [25]. Accordingly, MacIntyre and Moran [26] claimed that MI is coupled with motor execution, and thus that movement is possible
during imagined actions. Practically, enhancing imagery effectiveness by incorporating movement
during MI has been promoted early on in applied studies [27,28], and further discussed in theoretical models of imagery [6]. For instance, Holmes and Collins [6] stated that athletes should be actively involved in the imagery experience, for example
by involving sporting implements and making movements as necessary. Despite this previous
study, however, few experiments examined the association of MI with movement, whether
it is moving while imagining or imagining while moving. Vergeer and Roberts [29] investigated the effectiveness of performing MI during stretching, by asking participants
imagining leg movements during stretching, i.e. continuously flexing the knee and
bringing the heels toward the buttocks. They found a positive correlation between
improved flexibility and vividness ratings, hence suggesting that coupling MI with
stretching might have contributed to extend the range of motion or increase the duration
of the stretch. In a seminal paper, Callow et al. [21] later provided evidence that high level junior skiers who moved their body from side
to side during MI (dynamic imagery group), as if they were actually racing, experienced
the most vivid imagery and increased their confidence to perform the task. Other authors
also lend support for the dynamic aspect of imagery, and showed that moving during
imagery might result in greater improvements in performance compared to remaining
motionless [30]. A more recent study confirmed the beneficial role of gesturing during spatial problem
solving, although MI should not be confounded with spatial problem solving [31]. Specifically, the authors provided evidence that performing spontaneous hand movements
during mental rotation improved performance. The authors argued that the production
of similar co-thought gestures could facilitate other types of concurrent mental tasks
- such as MI - as well. Finally, as underlined by Lorey et al. [32], we are all familiar with pictures of athletes moving while imagining their subsequent
performance during pre-performance routines. While athletes claim that moving may
prime and facilitate MI, whether coupling MI and actual movement contributes to both
improving subsequent motor performance and achieving temporal congruence between MI
and motor performance has not yet been experimentally addressed.

The present study was designed to determine whether coupling MI with actual movement
(dynamic imagery) impacts motor performance to a greater extent than performing MI
without any overt body movement, and further contributes to achieve the temporal congruence
between MI and motor performance. Based on the assumption that MI and overt movement
are intimately related one to another both at the behavioral [25,26] and neurophysiological level [33], we postulated that coupling MI with actual movement might lead to improvements in
technical aspects compared to performing MI while remaining motionless and further
result in better temporal congruence between MI and actual times.

Methods

We used a within-subjects design allowing reduction in error variance associated with
individual differences. However, to avoid that participation in one imagery condition
affects performance in the other imagery condition, all MI trials were scheduled in
a random order.

Participants

A sample of high jumpers was recruited for the experiment as this motor skill is appropriate
for imagery training [34], and elite high jumpers frequently move while imagining their motor performance during
pre-performance routines. A total of 12 right-handed healthy high jumpers aged between
16 and 25 years old (mean age: 20.42 ± 3.61 years, 6 women) took part in the study,
which was approved by the Research Ethics Committee of the University. All athletes
were competing at national level events since 5 to 14 years, and with personal bests
ranging from 156 cm to 218 cm. They were free of any recent injury affecting motor
skills, balance, and had normal or corrected-to-normal vision. The procedure of the
experiment was explained to the participants, but no information was provided about
the objectives of the study or the dependent variables of interest.

Procedure and motor task

A first session was scheduled one week before the experiment to select the athletes
and determine their knowledge about MI. In particular, they were questioned about
the frequency and the nature of their imagery use, in order to exclude athletes who
regularly performed imagery routines including movements, and/or who would have been
unfamiliar with motionless imagery. Participants were also given descriptions of internal
visual imagery, external visual imagery, and kinaesthetic imagery, and were advised
that they will be able using kinaesthetic imagery in combination with whichever visual
support they found beneficial. All athletes self-reported using more frequently and
easily internal visual imagery along with kinaesthetic imagery. This combination was
therefore considered in the imagery scripts (see below).

The individual imagery ability of the participants was evaluated to ensure that the
sample did not include athletes with extremely high or low imagery ability, which
could have influenced the capacity to imagine in real time. The revised version of
the Movement Imagery Questionnaire (MIQ-R, [35]) was completed to measure the individual ability to form kinaesthetic and visual
mental images. The MIQ-R consists of an 8-item self-report questionnaire, in which
the participants rate the vividness of their mental representation using two 7-point
scales. We measured the individual ability to form visual images using the first series
of items (from 1 = “very hard to see” to 7 = “very easy to see”), the ability to perceive the sensations usually elicited by the movement during
kinaesthetic imagery with the second (from 1 = “very hard to feel” to 7 = “very easy to feel”). The MIQ-R has demonstrated adequate reliability and validity with alpha coefficients
of .79 for both subscales.

In accordance with the coaches, athletes were asked to imagine and actually jump over
a bar placed at 90% of their personal best, which had been performed during the season.
After four warm-up jumps, each athlete randomly performed a total of 10 actual jumps
and 10 MI trials within a single practice session. Practically, the first trial was
always a physical practice trial, in order to avoid participants imagining doing a
task without having performed it physically beforehand. Half of the MI trials were
performed while remaining motionless (motionless imagery), the other five trials being coupled with actual movement (dynamic imagery), i.e. athletes were asked to freely mimic the actual jump phases with their arms.
All participants performed MI in a position which was compatible with the motor skill,
i.e. in a standing position. Practically, we define dynamic imagery as a specific
sequence of MI which is accompanied by external movements miming in part those which
are mentally represented, in particular specific movement features related to temporal
or spatial invariance. Athletes were thus asked to mimic the actual movement using
simple upper-limb movements, but without engaging in the actual motor act and while
keeping the lower limbs motionless. The main functional aim of associating movement
to MI was to provide sensory feedback including somatosensory inputs likely to facilitate
the mental representation of the jump, and further help participants to formalize
the spatio-temporal configuration of the movement. Specifically, movements performed
during MI brought temporal boundaries, and thus had a temporal function to facilitate
calibration of time. Finally, lower-limb movements were excluded to limit the intensity
of the motor act during the mental representation (Figure 1). More generally, athletes were asked to consider the body as a generator of forces,
and therefore to combine internal visual imagery with kinaesthetic imagery. A detailed
imagery script based on previously published imagery research was read to ensure that
the participants followed similar instructions throughout MI sessionsa. To collect MI times, participants hold a timer in their non-dominant hand to ensure
that chronometric measures reflected only the mental representation of the movement,
and did not include other static images such as the preparation phase. Before the
experiment, we checked that participants did not feel uncomfortable with this procedure.

Measures

Three outcome measures were used as dependent variables to evaluate the efficacy of
MI. The temporal congruence between MI and physical performance was first recorded
as a reliable marker of MI accuracy [36-38]. Actual and MI times were thus recorded to test the individual ability to imagine
in real time. Actual times were recorded by the same experimenter, whereas MI times
were recorded by the athletes themselves, who triggered a timer as early as they imaged
the first move, and stopped the timer at the end of the jump, when falling down on
the carpet. They never received any feedback on MI times during the session to prevent
any influence on subsequent trials. Secondly, the number of successful jumps was considered
for the motionless imagery condition vs. the dynamic imagery condition. Thirdly, motor
performance was evaluated by considering the number of successful trials and by providing
efficiency ratings of technical motor skill components that are known to influence
jumping height. This latter evaluation was made by two expert trainers known for their
expertise in high jump. These measures were adequate as MI has been shown to impact
technique without necessarily resulting in immediate higher jump height [34]. To do so, athletes were filmed by a digital video camera (SANYO VPC-HD2000A, 30
Hz). Then, the two experts, who were not aware of the detailed experimental conditions,
and did not have a chance to see the athlete during MI, rated the quality of the jump.
To match live conditions, they independently watched each jump only once, and then
rated each trial using a 0 (poorest performance) to 10 (best performance) scale. For
each of the four selected performance items, marks of both experts were averaged to
provide a global score. Experts first rated the quality of the run approach before the curve, related to the amount of speed and the number and stride frequency.
The second item was the quality of the curve, including four to six strides. The quality of the impulsion was rated with reference to the take-off angle, body segments alignment and knee
position of the free limb. Finally, bar clearance was rated by evaluating the effectiveness of the movements of shoulders, knees and
feet. An overall technique score was also considered by averaging the four subscores
provided by the two experts.

Finally, individual debriefings were scheduled to control that MI instructions were
respected, and to determine whether participants encountered difficulty in forming
mental images. Accordingly, participants were required to rate the vividness of the
mental images they attempted to form during each condition, using a Likert-type scale
(from 1 = “unclear and inaccurate mental representation” to 6 = “perfectly clear and vivid mental representation”). They were also asked to report the experimental condition in which they formed
more easily mental images of the movement.

Data analysis

There was no significant gender difference on MI and actual times or on any rating
provided by the two experts, and thus there was no need to subdivide the group by
gender. One-way repeated measures analyses of variance (ANOVA) with two conditions
(motionless imagery vs. corresponding actual times, and dynamic imagery vs. corresponding
actual times, respectively) were performed to compare chronometric data. Repeated
measures ANOVAs were also computed to compare the number of successful jumps (“hit/miss”),
the overall technique score, and expert ratings in each experimental condition. Data
were then split into hits and misses and an additional 2 (Dynamic vs. Motionless imagery)
x 2 (Hit vs. Miss) repeated measure ANOVA was performed to compare actual and MI times.
Effect sizes, including partial eta-squared (η2) for ANOVA results are also provided. The results are presented as a mean (standard
deviation), and a level of p < 0.05 was considered critical for assigning statistical significance.

Results

Individual imagery ability

Mean MIQ-R scores (SD) were 39.50 (3.90). Mean score was 21.58 (1.98) for the visual
subscale, and 17.92 (2.78) for the kinaesthetic subscale. Visual scores were higher
than kinaesthetic scores (F(1,11) = 20.02, p < 0.001, η2 = .64). There was no participant with extremely high or low MIQ-R score (two SD above
or below the mean), and current MIQ-R mean scores were comparable to those observed
in previous MI studies [15,23].

Motor imagery and actual times

When MI was performed while remaining motionless, mean MI time was 5.12 s (0.88),
and mean corresponding actual time was 4.24 s (0.78). The ANOVA revealed that this
difference reached significance (F(1,11) = 24.72, p < 0.001, η2 = 0.69, Figure 2). When MI was coupled with actual movement, mean MI time was 4.26 s (0.79), and mean
corresponding actual time was 4.25 s (0.62). The ANOVA did not reveal any difference
between these times (F(1,11) = 0.02, p = 0.91, η2 = 0.001, Figure 2).

Figure 2.Mean (SD) Actual and motor imagery times. A significant difference was found between imagery and actual times when participants
performed motionless imagery. In contrast, they achieved temporal congruence during
dynamic imagery. ***: p < 0.001; NS: non-significant.

Assessment of imagery use

During the debriefings following MI sessions, all participants reported using motor
imagery as outlined in the scripts. All participants combined internal visual, auditory,
and kinaesthetic imagery without switching to external visual imagery, nor changing
the imagery script to suit individual needs. Accordingly, they were able to report
the series of movements with an explicit knowledge of each key-component of the physical
execution. Finally, respective mean ratings given by athletes when evaluating the
vividness of MI were 4.67 (0.98) during dynamic imagery and 3.58 (1.24) during motionless
imagery. The ANOVA revealed that the difference reached significance (F(1,11) = 14.19, p < 0.003, η2 = 0.56).

Discussion

The present study was designed to test whether integrating actual movement during
MI was likely to reinforce its well-known beneficial effects, and whether it may contribute
to achieve the temporal congruence. The main results revealed that moving while imagining
enhanced the quality and the whole timing of MI and, more particularly, the temporal
exactness of the approach run before the take-off of the jumping. The technical efficacy
of the jump was also improved, along with an increased number of successful trials,
and athletes reported forming mental images of the movement more easily and accurately
during the dynamic imagery condition. Altogether, these data support that coupling
MI with actual movement might contribute to reinforce MI quality and, therefore, its
expected efficacy.

Among the important prerequisites in developing MI training programs, there is now
ample evidence that athletes must achieve a temporal congruence between MI and physical
practice when they use MI to perform/rehearse movements [16,37] for reviews]. The difficulty to preserve the temporal features of the movement during
MI has also been taken as imagery impairment [38,39], and recording MI time is a reliable technique for assessing MI ability [40]. Interestingly, present findings provided evidence that coupling MI with actual movement-related
gestures, i.e. performing dynamic imagery resulted in a better temporal congruence
between MI and physical practice than performing MI while remaining motionless, hence
suggesting that MI was temporally more accurate. Dynamic imagery provides time boundaries
that would probably make the preparation phase before execution more effective. This
temporal accuracy came probably from subdividing the whole movement into several sub-sequences
associated with time boundaries, which are mentally reproduced, thus giving temporal
references to athletes. Achieving such temporal congruence is necessary as changes
in imagery speed can rapidly affect the subsequent actual speed [14], even for highly automated motor tasks where the duration is very much set and controlled
[15,16]. During high jump, athletes must visualize run-up without any feedback regarding
the optimal horizontal velocity and adjustment of the length, height, and speed of
their strides to prepare the take-off. Interestingly, present data suggest that dynamic
imagery helped them to calibrate the jump, and more particularly the run-up, through
a greater internal representation of its rhythm and tempo. The improved temporal accuracy
could also result in increased imagery vividness and therefore a richer representation
displayed in participants’ working memory [21]. Practically, the spatio-temporal features of the task are likely to be more closely
reproduced when athletes mimic their performance during MI, which might theoretically
contribute to improve subsequent actual jumps. Experimental validation of this working
hypothesis will certainly be the next step of dynamic imagery research.

As suggested by Olsson et al. [34], motor performance was not only measured in terms of successful or missed jump but
also using critical technical components that influence jumping height. Data first
showed that the rate of successful jumps tended to be better when coupling MI with
actual movement than when performing motionless MI. The comparison of expert ratings
measuring the technical quality of the jump confirmed the benefits provided by the
dynamic imagery condition. The most significant differences were observed during the
approach and the curve, hence supporting that moving while imagining contributes to
better calibrate the run-up. Hence, present findings confirmed that MI is beneficial
for skills that require complex movements such as bar clearance [34,41], but also supported its efficacy for enhancing the internalization and calibration
of the approach, which is also a critical factor of performance, albeit less complex
in terms of technique.

Previous data showed that MI is a cost-effective and valuable complement, but not
a substitute, to physical training, and that combining MI and subsequent physical
practice is more efficient than physical practice or MI alone [7,9,42]. Interestingly, looking at the effect of MI on motor recovery even proposed that
the benefits of MI are essentially due to combined physical and mental practice, while
MI alone does not necessarily result in greater performance [43]. In accordance with these assumptions, and based on present data as well as suggestions
from previous researchers [7,21,26,27,29-31], we state that using dynamic imagery, i.e. performing simple upper-limb movements
which integrate mainly temporal features of the actual practice during MI, is a potentially
fruitful direction to perform MI with important advantages. First, moving provides
actual feedback, thus offering an effective solution to the main limitation of MI,
that is, the absence of proprioceptive feedback. Accordingly, we postulate that even
if athletes only mimic their actual performance with their arms, such limited feedback
is likely to improve the individual ability to perform kinaesthetic imagery. This
hypothesis was somewhat confirmed by athletes’ self-estimation of their MI vividness.
They significantly reported forming more accurate mental images of the movement while
moving than while remaining motionless. Second, it might contribute to improve the
ability to achieve temporal congruence between MI and actual performance. In the case
of high jump, this is particularly effective for the run-up. Third, coupling MI with
actual practice is in accordance with the motor cognition approach supporting that
there is a continuum between motor preparation/execution and MI.

Interestingly, we observed that performing dynamic imagery is beneficial in experienced
athletes, while one might have expected a more limited effect due to such level of
expertise. We believe that moving while imagining is likely to enhance the mental
representation and the calibration of the run-up, which usually remains a difficult
task even in confirmed athletes. Indeed, athletes must resolve a complex relationship
between the speed of the approach running and the vertical velocity to be produced
for jumping. Moving while imagining might therefore contribute to stabilize a given
tempo for this part of the whole movement. Practically, this result suggests that
dynamic imagery might be used regardless of the level of expertise.

For a more theoretical viewpoint, we postulate that moving while imagining may have
emphasized the degree of behavioral matching, and possibly the functional equivalence
between MI and motor performance, which may contribute to explain the positive effects
of dynamic imagery. As suggested by the PETTLEP model of MI, interventions should
simulate, as closely as possible, all aspects of participants’ execution situations
[44]. Allowing athletes to perform dynamic imagery, at least in some occasions, might
thus help them to achieve this goal. Obviously, considering that MI and action can
occur simultaneously also raises some theoretical concerns. First, we state that athletes
could move while they imagine their motor performance, which is conceptually different
from imagining while they are moving. In the first case, limited motor execution would
merely supplement the MI input [26], while in the second, MI might occur as an epiphenomenon during the motor execution
process. Second, one may question whether dynamic imagery is a kind of imagery practice
per se, strictly speaking, as it challenges the common belief that MI occurs in the absence
of sensory input. Nikulin et al. [45] introduced the concept of quasi-movements, defined as volitional movements which
are minimized by the participant to such an extent that finally they become undetectable
by objective measures. Interestingly, they hypothesized that the procedure of learning
how to perform quasi-movements (by the successive reduction of movement strength to
a complete muscular quiescence) might represent a transition process between motor
execution and MI. As outlined by MacIntyre and Moran [26], we state that in every case, performing dynamic imagery requires to reconsider our
definitions of MI to encompass movements that can occur during mental practice.

Spurred by these findings, determining the efficacy of dynamic imagery in larger samples
and during competition settings is warranted. Some limitations are associated with
this study. First, the sample size was rather small with 12 athletes. A second, and
potentially more serious limitation, is that only five trials were performed in each
imagery condition, thus precluding from general conclusions in terms of performance
enhancement. Despite this, the improvement of the technical execution of the motor
skill promotes the use of dynamic imagery, and future studies should test this working
hypothesis experimentally. Unexpectedly, athletes passed the bar in few attempts,
although we enrolled qualified jumpers. We might explain this result by the fact that
they were asked to jump over a bar placed at 90% of their personal best, which had
been performed lately during the previous competition period. As the experiment was
scheduled early in the new competition period, we assume they still did not achieve
their optimal level of performance, and therefore the level of difficulty was probably
set slightly over 90% of their personal best previous performance. As another limitation
of our study, we must acknowledge that we reported the effectiveness of dynamic imagery
of a high-technical sporting skill. Although this finding is of importance, we must
also consider more simple movements which could be easily learnt in less time and
performed by healthy participants who are not necessarily sport athletes. Finally,
we did not look at whether MI might contribute to improve motor performance after
a training period, and did not include a control condition which is usually essential
before drawing general conclusions. Due to the characteristics of the sample (level
of expertise, number of athletes), as well as time lack which prevented us from spanning
the study over a longer period during the new competition period, we were not able
including a control condition. Including a condition with performance of actual movement
without any MI may thus be particularly helpful in future studies.

Conclusions

The present within-subjects design showed that performing dynamic imagery might be
of interest in a sample of athletes. Firstly, integrating some movements during MI
may contribute to improve the ability to achieve temporal congruence between MI and
actual performance, which has been shown to positively influence the efficacy of MI.
Secondly, data tend to suggest that the technical efficacy of the jump also improved,
along with an increased number of successful trials, therefore opening a way for fruitful
imagery applications in such populations of athletes.

Consent

Written informed consent was obtained from the participant for publication of this
report and any accompanying images.

Endnotes

aA copy of the imagery script is available from the corresponding author upon request.

Competing interests

The authors declare that they have no competing interests.

Authors’ contributions

AG conception and design, data analysis and interpretation, writing of the manuscript,
final approval of the submitted version. KM Conception and design, data acquisition
and collection. CC Conception and design, data analysis and interpretation, revision
of the manuscript. All authors read and approved the final manuscript.